Data set to accompany manuscript "Behavioural evidence of a humidistat: a temperature-compensating mechanism of hydroregulation"
Bibliographic record
Abstract
1. Water availability on land fluctuates both spatially and temporally, making the ability to control hydration state essential for terrestrial species. This is especially true in amphibians, which are more susceptible to dehydration than other vertebrates. Here, we used a laboratory humidity gradient to test how temperature (17°C vs. 22°C) affected behavioural hydroregulation in the spotted salamander (Ambystoma maculatum). 2. We found that salamanders defended a constant vapour pressure deficit (VPD), which was achieved by altering relative humidity (RH) selection between temperatures. Targeting a higher RH at 22°C than at 17°C possibly compensates for increased evaporative demand at higher temperatures, indicating a temperature-compensating behavioural mechanism. 3. Salamanders that selected higher VPDs experienced greater rates of evaporative water loss (EWL), with larger individuals showing higher EWL rates than smaller ones, even after accounting for temperature effects. Together, these results highlight a trade-off among body size, humidity preference, and desiccation tolerance. Salamanders also rehydrated faster at 22°C than at 17°C, showcasing temperature-dependent differences in water uptake rates. 4. Our findings demonstrate that field measurements such as RH alone are insufficient to predict behaviours of A. maculatum, since their behavioural preferences are mediated by how they manage water loss biophysically, rather than through simple meteorological measurements. 5. Therefore, ecophysiological measures should be considered in any field studies assessing habitat or microhabitat usage. Ultimately, our study underscores the complexity of amphibian hydroregulation and emphasises the critical role of behavioural strategies in maintaining hydration state.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.731 | 0.355 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".